An Efficient Method of Training Small Models for Regression Problems with Knowledge Distillation

28 February 2020

Papers citing "An Efficient Method of Training Small Models for Regression Problems with Knowledge Distillation"

8 / 8 papers shown

Title
Wing Loss for Robust Facial Landmark Localisation with Convolutional Neural Networks Zhenhua Feng J. Kittler Muhammad Awais P. Huber Xiaojun Wu CVBM 48 399 0 17 Nov 2017
A Closer Look at Memorization in Deep Networks Devansh Arpit Stanislaw Jastrzebski Nicolas Ballas David M. Krueger Emmanuel Bengio ... Tegan Maharaj Asja Fischer Aaron Courville Yoshua Bengio Simon Lacoste-Julien TDI 120 1,814 0 16 Jun 2017
Understanding deep learning requires rethinking generalization Chiyuan Zhang Samy Bengio Moritz Hardt Benjamin Recht Oriol Vinyals HAI 320 4,624 0 10 Nov 2016
Wide Residual Networks Sergey Zagoruyko N. Komodakis 318 7,971 0 23 May 2016
Deep Compression: Compressing Deep Neural Networks with Pruning, Trained Quantization and Huffman Coding Song Han Huizi Mao W. Dally 3DGS 239 8,821 0 01 Oct 2015
Robust Optimization for Deep Regression Vasileios Belagiannis Christian Rupprecht G. Carneiro Nassir Navab 3DH 145 180 0 25 May 2015
FitNets: Hints for Thin Deep Nets Adriana Romero Nicolas Ballas Samira Ebrahimi Kahou Antoine Chassang C. Gatta Yoshua Bengio FedML 282 3,870 0 19 Dec 2014
Do Deep Nets Really Need to be Deep? Lei Jimmy Ba R. Caruana 160 2,117 0 21 Dec 2013